Radical Uncertainty(근원적 불확실성)

by John Kay (Author, University of Oxford), Mervyn King (Author, New York University, London School of Economics)

 

[ radical uncertainty의 정의 ]

 

Radical uncertainty concerns events whose determinants are insufficiently understood for probabilities to be known or forecasting possible.

 

(pp.14)

We have chosen to replace the distiction between risk and uncertainty deployed by Knight and Keynes with a distiction between resolvable and radical uncertainty. Resolvable uncertainty is uncertainty which can be removed by looking something up (...). or which can be represented by a known probability distribution of outcomes (the spin of a roulette wheel). With radical uncertainty, however, there is no similar means of resolving the uncertainty - we simply do not know.

Radical uncertainty has many dimenstions: obscurity; ignorance; vagueness; ambiguity; ill-defined probelms; and a lack of information that in some cases but not all we might hope to rectify at a future date. These aspects of uncertainty are the stuff of everyday experience.

Radical uncertainty cannot be described in the probablistic terms applicable to a game of chance. It is not just that we do not know what will happen. We often do not even know the kinds of things that might happen.

When we describe radical uncertainty we are not talking about 'long tails' - imaginalble and well-defined events whose low probability can be estimated, such as a long losing streak at roulette. 

 

<참고> risk와 uncertainty의 차이

risk: measurabe uncertainty(Knight), calculable probability(Keynes)

 

[ Quotes from this book ]

 

(pp. 100)

As Edward Leamer, the distinguished American econometrician, has emphasised, 'statistical inference is and must forever remain an opinion'. Deciding which infromation is relevant to a decision is a matter of opinion - or, as we would prefer to describe it, judgement.

* Leamer, E. E. (1983) "Let't take the con out of Econometrics" American Economic Reivew, vol. 73, no. 1

 

(pp. 259)

Hausman quickly demolished Friedman's argument, as many others have done, by pointing out that the premises of a theory are every bit as much predictions of that theory as deductions from those premises.

 

(pp. 349)

Radical uncertainty and non-stationarity go hand in hand. There is no stable structure of the world about which we could learn from past experience and use to extrapolate future behaviour. 

...

As a result, the models used by central banks perform quite well when nothing very much is happening and fail dramatically when something big occurs - precisely the moment when the model might have something to offer beyond mere extrapolation of the past. 

 

(pp. 351)

When discovering the next big thing, Steve Jobs was not selecting from a menu of existing options, but using his imagination to create something completely new. That is the essence of radical uncertainty.

 

(pp. 382)

People who know only economics do not know much about economics.